Basic helix-loop-helix pioneer factors interact with the histone octamer to invade nucleosomes and generate nucleosome-depleted regions.

Nucleosomes drastically limit transcription factor (TF) occupancy, while pioneer transcription factors (PFs) somehow circumvent this nucleosome barrier. In this study, we compare nucleosome binding of two conserved S. cerevisiae basic helix-loop-helix (bHLH) TFs, Cbf1 and Pho4. A cryo-EM structure of Cbf1 in complex with the nucleosome reveals that the Cbf1 HLH region can electrostatically interact with exposed histone residues within a partially unwrapped nucleosome. Single-molecule fluorescence studies show that the Cbf1 HLH region facilitates efficient nucleosome invasion by slowing its dissociation rate relative to DNA through interactions with histones, whereas the Pho4 HLH region does not. In vivo studies show that this enhanced binding provided by the Cbf1 HLH region enables nucleosome invasion and ensuing repositioning. These structural, single-molecule, and in vivo studies reveal the mechanistic basis of dissociation rate compensation by PFs and how this translates to facilitating chromatin opening inside cells.

Time to add screening for financial hardship as a quality measure?

Cancer treatment is associated with financial hardship for many patients and families. Screening for financial hardship and referrals to appropriate resources for mitigation are not currently part of most clinical practices. In fact, discussions regarding the cost of treatment occur infrequently in clinical practice. As the cost of cancer treatment continues to rise, the need to mitigate adverse consequences of financial hardship grows more urgent. The introduction of quality measurement and reporting has been successful in establishing standards of care, reducing disparities in receipt of care, and improving other aspects of cancer care outcomes within and across providers. The authors propose the development and adoption of financial hardship screening and management as an additional quality metric for oncology practices. They suggest relevant stakeholders, conveners, and approaches for developing, testing, and implementing a screening and management tool and advocate for endorsement by organizations such as the National Quality Forum and professional societies for oncology care clinicians. The confluence of increasingly high-cost care and widening disparities in ability to pay because of underinsurance and lack of health insurance coverage makes a strong argument to take steps to mitigate the financial consequences of cancer.

How poverty is measured impacts who gets classified as impoverished.

We test whether the classification of households into poverty categories is meaningfully influenced by the poverty measurement approach that is employed. These classification techniques are widely used by governments, non-profit organizations, and development agencies for policy design and implementation. Using primary data collected in Ethiopia, Ghana, and Uganda, we find almost no agreement in how four commonly used approaches rank 16,150 households in terms of poverty status. This result holds for each country, for urban and rural households, and across the entire socio-economic distribution. Households' poverty rankings differ by an entire quartile on average. Conclusions about progress toward poverty alleviation goals may depend in large part on how poverty is measured.

Estimating the value of democracy relative to other institutional and economic outcomes among citizens in Brazil, France, and the United States.

How much do citizens value democracy? How willing are they to sacrifice their liberties and voting rights for growth, equality, or other social outcomes? We design a conjoint experiment in nationally representative surveys in Brazil, France, and the United States in which respondents choose between different societies that randomly vary in their economic outcomes (country income, income inequality, social mobility), political outcomes (democracy, public health insurance), and the level of personal income for each respondent. Our research allows us to estimate the respondents' willingness to trade off democracy for individual income (as well as other societal attributes). We find that, on average, individuals are strongly attached to democracy and a robust welfare state. They prefer to live in a country without free democratic elections only if their individual income multiplies by at least three times and in a country without public health insurance only if their individual income more than doubles. After estimating these preferences at the individual level for all respondents, we show that, although there is an authoritarian minority in all three countries, forming a nondemocratic majority (by offering more income and/or other goods to respondents) is very unlikely. Our findings imply that, contrary to a growing discussion about the crisis of democracy, liberal democratic values remain substantially robust in high and middle income democracies.

Freestanding lipid bilayer tensiometer for the study of mechanosensitive ion channels.

Mechanical forces modify the cell membrane potential by opening mechanosensitive ion channels. We report the design and construction of a lipid bilayer tensiometer to study channels that respond to lateral membrane tension, [Formula: see text] , in the range 0.2 to 1.4 [Formula: see text] (0.8 to 5.7 [Formula: see text] ). The instrument consists of a black-lipid-membrane bilayer, a custom-built microscope, and a high-resolution manometer. Values of [Formula: see text] are obtained from the determination of the bilayer curvature as a function of applied pressure by means of the Young-Laplace equation. We demonstrate that [Formula: see text] can be determined by calculating the bilayer radius of curvature from fluorescence microscopy imaging or from measurements of the bilayer's electrical capacitance, both yielding similar results. Using electrical capacitance, we show that the mechanosensitive potassium channel TRAAK responds to [Formula: see text] , not curvature. TRAAK channel open probability increases as [Formula: see text] is increased from 0.2 to 1.4 [Formula: see text] but open probability never reaches 0.5. Thus, TRAAK opens over a wide range of [Formula: see text] , but with a tension sensitivity about one-fifth that of the bacterial mechanosensitive channel MscL.

Scientific guidelines for evaluating the validity of forensic feature-comparison methods.

When it comes to questions of fact in a legal context-particularly questions about measurement, association, and causality-courts should employ ordinary standards of applied science. Applied sciences generally develop along a path that proceeds from a basic scientific discovery about some natural process to the formation of a theory of how the process works and what causes it to fail, to the development of an invention intended to assess, repair, or improve the process, to the specification of predictions of the instrument's actions and, finally, empirical validation to determine that the instrument achieves the intended effect. These elements are salient and deeply embedded in the cultures of the applied sciences of medicine and engineering, both of which primarily grew from basic sciences. However, the inventions that underlie most forensic science disciplines have few roots in basic science, and they do not have sound theories to justify their predicted actions or results of empirical tests to prove that they work as advertised. Inspired by the "Bradford Hill Guidelines"-the dominant framework for causal inference in epidemiology-we set forth four guidelines that can be used to establish the validity of forensic comparison methods generally. This framework is not intended as a checklist establishing a threshold of minimum validity, as no magic formula determines when particular disciplines or hypotheses have passed a necessary threshold. We illustrate how these guidelines can be applied by considering the discipline of firearm and tool mark examination.

Indentation induces instantaneous nuclear stiffening and unfolding of nuclear envelope wrinkles.

The nuclear envelope (NE) separates genomic DNA from the cytoplasm and regulates transport between the cytosol and the nucleus in eukaryotes. Nuclear stiffening enables the cell nucleus to protect itself from extensive deformation, loss of NE integrity, and genome instability. It is known that the reorganization of actin, lamin, and chromatin can contribute to nuclear stiffening. In this work, we show that structural alteration of NE also contributes to instantaneous nuclear stiffening under indentation. In situ mechanical characterization of cell nuclei in intact cells shows that nuclear stiffening and unfolding of NE wrinkles occur simultaneously at the indentation site. A positive correlation between the initial state of NE wrinkles, the unfolding of NE wrinkles, and the stiffening ratio (stiffness fold-change) is found. Additionally, NE wrinkles unfold throughout the nucleus outside the indentation site. Finite element simulation, which involves the purely passive process of structural unfolding, shows that unfolding of NE wrinkles alone can lead to an increase in nuclear stiffness and a reduction in stress and strain levels. Together, these results provide a perspective on how cell nucleus adapts to mechanical stimuli through structural alteration of the NE.

Quantum reality with negative-mass particles.

Physical interpretations of the time-symmetric formulation of quantum mechanics, due to Aharonov, Bergmann, and Lebowitz are discussed in terms of weak values. The most direct, yet somewhat naive, interpretation uses the time-symmetric formulation to assign eigenvalues to unmeasured observables of a system, which results in logical paradoxes, and no clear physical picture. A top-down ontological model is introduced that treats the weak values of observables as physically real during the time between pre- and post-selection (PPS), which avoids these paradoxes. The generally delocalized rank-1 projectors of a quantum system describe its fundamental ontological elements, and the highest-rank projectors corresponding to individual localized objects describe an emergent particle model, with unusual particles, whose masses and energies may be negative or imaginary. This retrocausal top-down model leads to an intuitive particle-based ontological picture, wherein weak measurements directly probe the properties of these exotic particles, which exist whether or not they are actually measured.

Fast backward steps and detachment of single kinesin molecules measured under a wide range of loads.

To understand force generation under a wide range of loads, the stepping of single kinesin molecules was measured at loads from -20 to 42 pN by optical tweezers with high temporal resolution. The optical trap has been improved to halve positional noise and increase bandwidth by using 200-nm beads. The step size of the forward and backward steps was 8.2 nm even over a wide range of loads. Histograms of the dwell times of backward steps and detachment fit well to two independent exponential equations with fast (~0.4 ms) and slow (>3 ms) time constants, indicating the existence of a fast step in addition to the conventional slow step. The dwell times of the fast steps were almost independent of the load and ATP concentration, while those of the slow backward steps and detachment depended on those. We constructed the kinetic model to explain the fast and slow steps under a wide range of loads.

Unveiling challenges in Mendelian randomization for gene-environment interaction.

Gene-environment (GxE) interactions play a crucial role in understanding the complex etiology of various traits, but assessing them using observational data can be challenging due to unmeasured confounders for lifestyle and environmental risk factors. Mendelian randomization (MR) has emerged as a valuable method for assessing causal relationships based on observational data. This approach utilizes genetic variants as instrumental variables (IVs) with the aim of providing a valid statistical test and estimation of causal effects in the presence of unmeasured confounders. MR has gained substantial popularity in recent years largely due to the success of genome-wide association studies. Many methods have been developed for MR; however, limited work has been done on evaluating GxE interaction. In this paper, we focus on two primary IV approaches: the two-stage predictor substitution and the two-stage residual inclusion, and extend them to accommodate GxE interaction under both the linear and logistic regression models for continuous and binary outcomes, respectively. Comprehensive simulation study and analytical derivations reveal that resolving the linear regression model is relatively straightforward. In contrast, the logistic regression model presents a considerably more intricate challenge, which demands additional effort.

Estimating the overall fraction of phenotypic variance attributed to high-dimensional predictors measured with error.

In prospective genomic studies (e.g., DNA methylation, metagenomics, and transcriptomics), it is crucial to estimate the overall fraction of phenotypic variance (OFPV) attributed to the high-dimensional genomic variables, a concept similar to heritability analyses in genome-wide association studies (GWAS). Unlike genetic variants in GWAS, these genomic variables are typically measured with error due to technical limitation and temporal instability. While the existing methods developed for GWAS can be used, ignoring measurement error may severely underestimate OFPV and mislead the design of future studies. Assuming that measurement error variances are distributed similarly between causal and noncausal variables, we show that the asymptotic attenuation factor equals to the average intraclass correlation coefficients of all genomic variables, which can be estimated based on a pilot study with repeated measurements. We illustrate the method by estimating the contribution of microbiome taxa to body mass index and multiple allergy traits in the American Gut Project. Finally, we show that measurement error does not cause meaningful bias when estimating the correlation of effect sizes for two traits.

Differential transcript usage analysis incorporating quantification uncertainty via compositional measurement error regression modeling.

Differential transcript usage (DTU) occurs when the relative expression of multiple transcripts arising from the same gene changes between different conditions. Existing approaches to detect DTU often rely on computational procedures that can have speed and scalability issues as the number of samples increases. Here we propose a new method, CompDTU, that uses compositional regression to model the relative abundance proportions of each transcript that are of interest in DTU analyses. This procedure leverages fast matrix-based computations that make it ideally suited for DTU analysis with larger sample sizes. This method also allows for the testing of and adjustment for multiple categorical or continuous covariates. Additionally, many existing approaches for DTU ignore quantification uncertainty in the expression estimates for each transcript in RNA-seq data. We extend our CompDTU method to incorporate quantification uncertainty leveraging common output from RNA-seq expression quantification tool in a novel method CompDTUme. Through several power analyses, we show that CompDTU has excellent sensitivity and reduces false positive results relative to existing methods. Additionally, CompDTUme results in further improvements in performance over CompDTU with sufficient sample size for genes with high levels of quantification uncertainty, while also maintaining favorable speed and scalability. We motivate our methods using data from the Cancer Genome Atlas Breast Invasive Carcinoma data set, specifically using RNA-seq data from primary tumors for 740 patients with breast cancer. We show greatly reduced computation time from our new methods as well as the ability to detect several novel genes with significant DTU across different breast cancer subtypes.

Multiple imputation of more than one environmental exposure with nondifferential measurement error.

Measurement error is common in environmental epidemiologic studies, but methods for correcting measurement error in regression models with multiple environmental exposures as covariates have not been well investigated. We consider a multiple imputation approach, combining external or internal calibration samples that contain information on both true and error-prone exposures with the main study data of multiple exposures measured with error. We propose a constrained chained equations multiple imputation (CEMI) algorithm that places constraints on the imputation model parameters in the chained equations imputation based on the assumptions of strong nondifferential measurement error. We also extend the constrained CEMI method to accommodate nondetects in the error-prone exposures in the main study data. We estimate the variance of the regression coefficients using the bootstrap with two imputations of each bootstrapped sample. The constrained CEMI method is shown by simulations to outperform existing methods, namely the method that ignores measurement error, classical calibration, and regression prediction, yielding estimated regression coefficients with smaller bias and confidence intervals with coverage close to the nominal level. We apply the proposed method to the Neighborhood Asthma and Allergy Study to investigate the associations between the concentrations of multiple indoor allergens and the fractional exhaled nitric oxide level among asthmatic children in New York City. The constrained CEMI method can be implemented by imposing constraints on the imputation matrix using the mice and bootImpute packages in R.

Improving comparative analyses of Hi-C data via contrastive self-supervised learning.

Hi-C is a widely applied chromosome conformation capture (3C)-based technique, which has produced a large number of genomic contact maps with high sequencing depths for a wide range of cell types, enabling comprehensive analyses of the relationships between biological functionalities (e.g. gene regulation and expression) and the three-dimensional genome structure. Comparative analyses play significant roles in Hi-C data studies, which are designed to make comparisons between Hi-C contact maps, thus evaluating the consistency of replicate Hi-C experiments (i.e. reproducibility measurement) and detecting statistically differential interacting regions with biological significance (i.e. differential chromatin interaction detection). However, due to the complex and hierarchical nature of Hi-C contact maps, it remains challenging to conduct systematic and reliable comparative analyses of Hi-C data. Here, we proposed sslHiC, a contrastive self-supervised representation learning framework, for precisely modeling the multi-level features of chromosome conformation and automatically producing informative feature embeddings for genomic loci and their interactions to facilitate comparative analyses of Hi-C contact maps. Comprehensive computational experiments on both simulated and real datasets demonstrated that our method consistently outperformed the state-of-the-art baseline methods in providing reliable measurements of reproducibility and detecting differential interactions with biological meanings.

On the reliability of individual economic rationality measurements.

A contemporary research agenda in behavioral economics and neuroeconomics aims to identify individual differences and (neuro)psychological correlates of rationality. This research has been widely received in important interdisciplinary and field outlets. However, the psychometric reliability of such measurements of rationality has been presumed without enough methodological scrutiny. Drawing from multiple original and published datasets (in total over 1,600 participants), we unequivocally show that contemporary measurements of rationality have moderate to poor reliability according to common standards. Further analyses of the variance components, as well as a allowing participants to revise previous choices, suggest that this is driven by low between-subject variance rather than high measurement error. As has been argued previously for other behavioral measurements, this poses a challenge to the predominant correlational research designs and the search for sociodemographic or neural predictors. While our results draw a sobering picture of the prospects of contemporary measurements of rationality, they are not necessarily surprising from a theoretical perspective, which we outline in our discussion.

Structured foraging of soil predators unveils functional responses to bacterial defenses.

Predators and their foraging strategies often determine ecosystem structure and function. Yet, the role of protozoan predators in microbial soil ecosystems remains elusive despite the importance of these ecosystems to global biogeochemical cycles. In particular, amoebae-the most abundant soil protozoan predator of bacteria-remineralize soil nutrients and shape the bacterial community. However, their foraging strategies and their role as microbial ecosystem engineers remain unknown. Here, we present a multiscale approach, connecting microscopic single-cell analysis and macroscopic whole ecosystem dynamics, to expose a phylogenetically widespread foraging strategy, in which an amoeba population spontaneously partitions between cells with fast, polarized movement and cells with slow, unpolarized movement. Such differentiated motion gives rise to efficient colony expansion and consumption of the bacterial substrate. From these insights, we construct a theoretical model that predicts how disturbances to amoeba growth rate and movement disrupt their predation efficiency. These disturbances correspond to distinct classes of bacterial defenses, which allows us to experimentally validate our predictions. All considered, our characterization of amoeba foraging identifies amoeba mobility, and not amoeba growth, as the core determinant of predation efficiency and a key target for bacterial defense systems.

Wide-field optical imaging of electrical charge and chemical reactions at the solid-liquid interface.

From molecules and particles to macroscopic surfaces immersed in fluids, chemical reactions often endow interfaces with electrical charge which in turn governs surface interactions and interfacial phenomena. The ability to measure the electrical properties of a material immersed in any solvent, as well as to monitor the spatial heterogeneity and temporal variation thereof, has been a long-standing challenge. Here, we describe an optical microscopy-based approach to probe the surface charge distribution of a range of materials, including inorganic oxide, polymer, and polyelectrolyte films, in contact with a fluid. The method relies on optical visualization of the electrical repulsion between diffusing charged probe molecules and the unknown surface to be characterized. Rapid image-based measurements enable us to further determine isoelectric points of the material as well as properties of its ionizable chemical groups. We further demonstrate the ability to optically monitor chemically triggered surface charge changes with millisecond time resolution. Finally, we present a scanning-surface probe technique capable of diffraction-limited imaging of spatial heterogeneities in chemical composition and charge over large areas. This technique will enable facile characterization of the solid-liquid interface with wide-ranging relevance across application areas from biology to engineering.

Thickness-Dependent Magnetic Breakdown in ZrSiSe Nanoplates.

We report a study of thickness-dependent interband and intraband magnetic breakdown by thermoelectric quantum oscillations in ZrSiSe nanoplates. Under high magnetic fields of up to 30 T, quantum oscillations arising from degenerated hole pockets were observed in thick ZrSiSe nanoplates. However, when decreasing the thickness, plentiful multifrequency quantum oscillations originating from hole and electron pockets are captured. These multiple frequencies can be explained by the emergent interband magnetic breakdown enclosing individual hole and electron pockets and intraband magnetic breakdown within spin-orbit coupling (SOC) induced saddle-shaped electron pockets, resulting in the enhanced contribution to thermal transport in thin ZrSiSe nanoplates. These experimental frequencies agree well with theoretical calculations of the intriguing tunneling processes. Our results introduce a new member of magnetic breakdown to the field and open up a dimension for modulating magnetic breakdown, which holds fundamental significance for both low-dimensional topological materials and the physics of magnetic breakdown.

Diffusion-Dominated Luminescence Dynamics of CsPbBr3 Studied Using Cathodoluminescence and Microphotoluminescence Spectroscopy.

Time-resolved or time-correlation measurements using cathodoluminescence (CL) reveal the electronic and optical properties of semiconductors, such as their carrier lifetimes, at the nanoscale. However, halide perovskites, which are promising optoelectronic materials, exhibit significantly different decay dynamics in their CL and photoluminescence (PL). We conducted time-correlation CL measurements of CsPbBr3 using Hanbury Brown-Twiss interferometry and compared them with time-resolved PL. The measured CL decay time was on the order of subnanoseconds and was faster than PL decay at an excited carrier density of 2.1 × 1018 cm-3. Our experiment and analytical model revealed the CL dynamics induced by individual electron incidences, which are characterized by highly localized carrier generation followed by a rapid decrease in carrier density due to diffusion. This carrier diffusion can play a dominant role in the CL decay time for undoped semiconductors, in general, when the diffusion dynamics are faster than the carrier recombination.

Mechanical Tester Driven by Surface Tension.

The measurement of in-plane mechanical properties, such as Young's modulus and strength, of thin and stretchable materials has long been a challenge. Existing measurements, including wrinkle instability and nano indentation, are either indirect or destructive, and are inapplicable to meshes or porous materials, while the conventional tension test fails to measure the mechanical properties of nanoscale films. Here, we report a technique to test thin and stretchable films by loading a thin film afloat via differential surface tension and recording its deformation. We have demonstrated the method by measuring the Young's moduli of homogeneous films of soft materials including polydimethylsiloxane and Ecoflex and verified the results with known values. We further measured the strain distributions of meshes, both isotropic and anisotropic, which were otherwise nearly impossible to measure. The method proposed herein is expected to be generally applicable to many material systems that are thin, stretchable, and water-insoluble.